Biostatistics × R × Data Visualization
@rforbiostats.bsky.social
R-powered data visualization for biostatistics and health sciences.
From raw data to publication-ready figures.
#r #rstats #dataviz #healthdata #posit #positron
From raw data to publication-ready figures.
#r #rstats #dataviz #healthdata #posit #positron
Pinned
I work in biostatistics using R to analyze and visualize health data.
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
January 2, 2026 at 5:47 PM
January 2, 2026 at 5:46 PM
January 2, 2026 at 5:46 PM
Biostatistics is not about finding significance.
It’s about estimating effects and uncertainty.
#rstats #biostatistics
It’s about estimating effects and uncertainty.
#rstats #biostatistics
January 2, 2026 at 5:46 PM
Biostatistics is not about finding significance.
It’s about estimating effects and uncertainty.
#rstats #biostatistics
It’s about estimating effects and uncertainty.
#rstats #biostatistics
I work in biostatistics using R to analyze and visualize health data.
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
January 2, 2026 at 5:44 PM
I work in biostatistics using R to analyze and visualize health data.
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
My goal is to make medical statistics clear, reproducible, and interpretable.
#rstats #biostatistics #healthdata
"p-value" don’t tell the whole story.
R makes effect sizes and uncertainty easier to report.
#rstats #biostats #medicalstats
R makes effect sizes and uncertainty easier to report.
#rstats #biostats #medicalstats
January 2, 2026 at 5:42 PM
"p-value" don’t tell the whole story.
R makes effect sizes and uncertainty easier to report.
#rstats #biostats #medicalstats
R makes effect sizes and uncertainty easier to report.
#rstats #biostats #medicalstats
Good biostatistics starts with data structure.
R encourages transparent workflows from raw data to results.
#rstats #healthdata #clinicalresearch
R encourages transparent workflows from raw data to results.
#rstats #healthdata #clinicalresearch
January 2, 2026 at 5:42 PM
Good biostatistics starts with data structure.
R encourages transparent workflows from raw data to results.
#rstats #healthdata #clinicalresearch
R encourages transparent workflows from raw data to results.
#rstats #healthdata #clinicalresearch
Clinical research moves faster when tables are reproducible.
gtsummary saves time without sacrificing rigor.
#rstats #gtsummary #clinicaldata
gtsummary saves time without sacrificing rigor.
#rstats #gtsummary #clinicaldata
January 2, 2026 at 5:41 PM
Clinical research moves faster when tables are reproducible.
gtsummary saves time without sacrificing rigor.
#rstats #gtsummary #clinicaldata
gtsummary saves time without sacrificing rigor.
#rstats #gtsummary #clinicaldata
Standardized tables reduce analytical noise.
gtsummary supports transparent and defensible medical statistics.
#rstats #gtsummary #openscience
gtsummary supports transparent and defensible medical statistics.
#rstats #gtsummary #openscience
January 2, 2026 at 5:41 PM
Standardized tables reduce analytical noise.
gtsummary supports transparent and defensible medical statistics.
#rstats #gtsummary #openscience
gtsummary supports transparent and defensible medical statistics.
#rstats #gtsummary #openscience
Readable tables lead to better decisions.
gtsummary turns complex medical data into interpretable summaries.
#rstats #healthdata #medicalstats
gtsummary turns complex medical data into interpretable summaries.
#rstats #healthdata #medicalstats
January 2, 2026 at 5:41 PM
Readable tables lead to better decisions.
gtsummary turns complex medical data into interpretable summaries.
#rstats #healthdata #medicalstats
gtsummary turns complex medical data into interpretable summaries.
#rstats #healthdata #medicalstats
Consistency matters in clinical reporting.
With gtsummary, tables stay aligned across analyses and revisions.
#rstats #clinicalresearch #reproducibility
With gtsummary, tables stay aligned across analyses and revisions.
#rstats #clinicalresearch #reproducibility
January 2, 2026 at 5:40 PM
Consistency matters in clinical reporting.
With gtsummary, tables stay aligned across analyses and revisions.
#rstats #clinicalresearch #reproducibility
With gtsummary, tables stay aligned across analyses and revisions.
#rstats #clinicalresearch #reproducibility
Clear summaries improve peer review.
gtsummary helps reviewers focus on results, not table formatting.
#rstats #gtsummary #peerreview #biostatistics
gtsummary helps reviewers focus on results, not table formatting.
#rstats #gtsummary #peerreview #biostatistics
January 2, 2026 at 5:40 PM
Clear summaries improve peer review.
gtsummary helps reviewers focus on results, not table formatting.
#rstats #gtsummary #peerreview #biostatistics
gtsummary helps reviewers focus on results, not table formatting.
#rstats #gtsummary #peerreview #biostatistics
Reproducibility starts with structure.
gtsummary keeps medical statistics clean, consistent, and publication-ready.
#rstats #gtsummary #clinicalresearch #researchtools
gtsummary keeps medical statistics clean, consistent, and publication-ready.
#rstats #gtsummary #clinicalresearch #researchtools
January 2, 2026 at 5:40 PM
Reproducibility starts with structure.
gtsummary keeps medical statistics clean, consistent, and publication-ready.
#rstats #gtsummary #clinicalresearch #researchtools
gtsummary keeps medical statistics clean, consistent, and publication-ready.
#rstats #gtsummary #clinicalresearch #researchtools
Good methods deserve clear reporting.
gtsummary supports standardized summaries and regression outputs in medical studies.
#rstats #gtsummary #clinicaldata #openscience
gtsummary supports standardized summaries and regression outputs in medical studies.
#rstats #gtsummary #clinicaldata #openscience
January 2, 2026 at 5:39 PM
Good methods deserve clear reporting.
gtsummary supports standardized summaries and regression outputs in medical studies.
#rstats #gtsummary #clinicaldata #openscience
gtsummary supports standardized summaries and regression outputs in medical studies.
#rstats #gtsummary #clinicaldata #openscience
From raw clinical data to decision-ready tables.
gtsummary bridges statistical analysis and scientific communication.
#rstats #biostats #scicomm #medicalstats
gtsummary bridges statistical analysis and scientific communication.
#rstats #biostats #scicomm #medicalstats
January 2, 2026 at 5:39 PM
From raw clinical data to decision-ready tables.
gtsummary bridges statistical analysis and scientific communication.
#rstats #biostats #scicomm #medicalstats
gtsummary bridges statistical analysis and scientific communication.
#rstats #biostats #scicomm #medicalstats
Manual table formatting is a reproducibility risk.
With gtsummary, clinical summary and regression tables stay transparent and consistent.
#rstats #healthdata #reproducibleresearch
With gtsummary, clinical summary and regression tables stay transparent and consistent.
#rstats #healthdata #reproducibleresearch
January 2, 2026 at 5:38 PM
Manual table formatting is a reproducibility risk.
With gtsummary, clinical summary and regression tables stay transparent and consistent.
#rstats #healthdata #reproducibleresearch
With gtsummary, clinical summary and regression tables stay transparent and consistent.
#rstats #healthdata #reproducibleresearch
library(gtsummary); data(trial)
trial |> tbl_summary(by = trt,
statistic = all_continuous() ~ "{median} [{p25},{p75}]") |> add_p()
#rstats #biostats #reproducibleresearch
trial |> tbl_summary(by = trt,
statistic = all_continuous() ~ "{median} [{p25},{p75}]") |> add_p()
#rstats #biostats #reproducibleresearch
January 2, 2026 at 5:37 PM
library(gtsummary); data(trial)
trial |> tbl_summary(by = trt,
statistic = all_continuous() ~ "{median} [{p25},{p75}]") |> add_p()
#rstats #biostats #reproducibleresearch
trial |> tbl_summary(by = trt,
statistic = all_continuous() ~ "{median} [{p25},{p75}]") |> add_p()
#rstats #biostats #reproducibleresearch
library(gtsummary); data(trial)
trial |> tbl_summary(by = trt, include = c(age, grade, response, marker)) |> add_n()
#rstats #healthdata #medicalstats
trial |> tbl_summary(by = trt, include = c(age, grade, response, marker)) |> add_n()
#rstats #healthdata #medicalstats
January 2, 2026 at 5:33 PM
library(gtsummary); data(trial)
trial |> tbl_summary(by = trt, include = c(age, grade, response, marker)) |> add_n()
#rstats #healthdata #medicalstats
trial |> tbl_summary(by = trt, include = c(age, grade, response, marker)) |> add_n()
#rstats #healthdata #medicalstats
library(gtsummary); data(trial)
trial |> tbl_summary(by=trt) |> add_p() |> add_overall()
#rstats #gtsummary #biostatistics #clinicalresearch #posit
trial |> tbl_summary(by=trt) |> add_p() |> add_overall()
#rstats #gtsummary #biostatistics #clinicalresearch #posit
January 2, 2026 at 5:31 PM
library(gtsummary); data(trial)
trial |> tbl_summary(by=trt) |> add_p() |> add_overall()
#rstats #gtsummary #biostatistics #clinicalresearch #posit
trial |> tbl_summary(by=trt) |> add_p() |> add_overall()
#rstats #gtsummary #biostatistics #clinicalresearch #posit
Clear tables matter in medical research.
gtsummary helps turn raw clinical data into reproducible, publication-ready results—without manual formatting.
#rstats #gtsummary #biostatistics #clinicalresearch
gtsummary helps turn raw clinical data into reproducible, publication-ready results—without manual formatting.
#rstats #gtsummary #biostatistics #clinicalresearch
January 2, 2026 at 5:30 PM
Clear tables matter in medical research.
gtsummary helps turn raw clinical data into reproducible, publication-ready results—without manual formatting.
#rstats #gtsummary #biostatistics #clinicalresearch
gtsummary helps turn raw clinical data into reproducible, publication-ready results—without manual formatting.
#rstats #gtsummary #biostatistics #clinicalresearch
surv_data <- data.frame(time = time, status = status, group = group)
fit <- survfit(Surv(time, status) ~ group, data = surv_data)
km_plot <- ggsurvplot()
#RStats #DataScience #Biostatistics #DataVisualization #RStudio
#Statistics #ggplot2
fit <- survfit(Surv(time, status) ~ group, data = surv_data)
km_plot <- ggsurvplot()
#RStats #DataScience #Biostatistics #DataVisualization #RStudio
#Statistics #ggplot2
January 2, 2026 at 1:34 PM
surv_data <- data.frame(time = time, status = status, group = group)
fit <- survfit(Surv(time, status) ~ group, data = surv_data)
km_plot <- ggsurvplot()
#RStats #DataScience #Biostatistics #DataVisualization #RStudio
#Statistics #ggplot2
fit <- survfit(Surv(time, status) ~ group, data = surv_data)
km_plot <- ggsurvplot()
#RStats #DataScience #Biostatistics #DataVisualization #RStudio
#Statistics #ggplot2
gtsummary is an R package for creating clear, publication-ready summary and regression tables—especially for medical and biostatistics research. It integrates seamlessly with tidyverse workflows and supports reproducible clinical research.
#rstats #gtsummary #biostatistics #clinicalresearch
#rstats #gtsummary #biostatistics #clinicalresearch
January 2, 2026 at 1:28 PM
gtsummary is an R package for creating clear, publication-ready summary and regression tables—especially for medical and biostatistics research. It integrates seamlessly with tidyverse workflows and supports reproducible clinical research.
#rstats #gtsummary #biostatistics #clinicalresearch
#rstats #gtsummary #biostatistics #clinicalresearch
library(gtsummary)
data(trial)
trial |>
tbl_summary(
by = trt,
statistic = all_continuous() ~ "{mean} ({sd})"
) |>
add_p() |>
add_overall()
data(trial)
trial |>
tbl_summary(
by = trt,
statistic = all_continuous() ~ "{mean} ({sd})"
) |>
add_p() |>
add_overall()
January 2, 2026 at 1:27 PM
library(gtsummary)
data(trial)
trial |>
tbl_summary(
by = trt,
statistic = all_continuous() ~ "{mean} ({sd})"
) |>
add_p() |>
add_overall()
data(trial)
trial |>
tbl_summary(
by = trt,
statistic = all_continuous() ~ "{mean} ({sd})"
) |>
add_p() |>
add_overall()
Want publication-ready tables in R with minimal effort?
gtsummary turns clinical & biostat data into clean, reproducible summary and regression tables. Perfect for papers & reports.
www.danieldsjoberg.com/gtsummary/
#rstats #gtsummary #biostatistics #healthdata #dataviz
gtsummary turns clinical & biostat data into clean, reproducible summary and regression tables. Perfect for papers & reports.
www.danieldsjoberg.com/gtsummary/
#rstats #gtsummary #biostatistics #healthdata #dataviz
Presentation-Ready Data Summary and Analytic Result Tables
Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function,...
www.danieldsjoberg.com
January 2, 2026 at 1:24 PM
Want publication-ready tables in R with minimal effort?
gtsummary turns clinical & biostat data into clean, reproducible summary and regression tables. Perfect for papers & reports.
www.danieldsjoberg.com/gtsummary/
#rstats #gtsummary #biostatistics #healthdata #dataviz
gtsummary turns clinical & biostat data into clean, reproducible summary and regression tables. Perfect for papers & reports.
www.danieldsjoberg.com/gtsummary/
#rstats #gtsummary #biostatistics #healthdata #dataviz